MEPSnet/IC Statistical Help
For each chart generated by MEPSnet/IC, a table is provided which lists the survey estimates shown in the chart and their corresponding standard errors (SE). These standard errors reflect the estimated sampling error associated with the estimate (i.e. potential error introduced because data were collected for only a sample of establishments).
Analysts frequently generate 95% confidence intervals to assess the precision of survey estimates. These intervals are computed as:
Estimate +/ 1.96*SE
MEPSnet/IC displays a 95 percent confidence interval for each estimate shown in the chart. A 95 percent confidence interval has the following general interpretation: applying the intervalestimating procedure to all possible samples, a statement that a given interval enclosed the true population mean would be correct 95 percent of the time. Therefore, one can be 95 percent sure that an interval constructed from one sample captures the true population mean.
As an example, the following chart and table generated using MEPSnet/IC shows the average total single premium levels from 201214 at privatesector establishments that offer health insurance. The estimated average premium in 2012 was $5,384, but the corresponding confidence interval was $5,384 +/ 1.96*27.83 (i.e. the interval ranges from $5,329.45.30 to $5,438.55).
Test of Significance
To interpret whether there has been a statistically significant change between 2 particular years, one can compute a zstatistic using the following formula:
For example, the zstatistic to assess whether the difference in average premiums between 2012 and 2014 is statistically significant would be computed as follows:
The threshold zstatistic for establishing statistical significance at the .05 level is 1.96. That is, if the calculated zstatistic is greater than 1.96 or less than –1.96, the estimates are significantly different at the .05 level. All values that are significant at the 0.05 level are marked with an *. For this example, the calculated zstatistic of 11.89 is greater than 1.96, so the difference between the two years is statistically significant.
The pvalue shown in the table below is the probability of having a zstatistic as large or larger than the one calculated from these estimates (or smaller in cases where the zstatistic is negative). When this pvalue is less than or equal to the 0.05 level of significance, then the difference is statistically significant at that level and is marked with an *. In our example, the pvalue associated with the zstatistic of 11.89 is very small (rounds to 0.00000) and thus this difference is statistically significant.
Year 
Average 
Std. Error 
2012 
5,384 
27.83 
2013 
5,571 
22.70 
2014 
5,832 
25.41 
zTest Showing the Significance of Change Between Years
Years Compared 
Average 
SE 
Joint SE 
zStatistic 
pValue (twotail) 
2012 
5,384 
27.83 
35.91 
5.19785 
0.00000* 
2013 
5,571 
22.70 
2012 
5,384 
27.83 
37.69 
11.87253 
0.00000* 
2014 
5,832 
25.41 
2013 
5,571 
22.70 
34.07 
7.65380 
0.00000* 
2014 
5,832 
25.41 
* Significant at 0.05 level
Average total single premium (in dollars) per enrolled employee at privatesector establishments that offer health insurance: United States
Years 
Average Premium 
1996 
1,992 
1997 
2,051 
1998 
2,174 
1999 
2,325 
2000 
2,655 
2001 
2,889 
2002 
3,189 
2003 
3,481 
2004 
3,705 
2005 
3,991 
2006 
4,118 
2007 
 
2008 
4,386 
2009 
4,669 
2010 
4,940 
2011 
5,222 
2012 
5,384 
2013 
5,571 
2014 
5,832 
 2007 data were not coleected for the Insurance Component.
